It’s been more than a month since the news about the human-like model to generate text (GPT-2) hit the media., If you haven’t paid much attention to this topic here is a short summary with useful reference materials.

To answer this question, let's take an example. We all learned to recognize colours by being introduced to the objects in those colours first. Strawberry, tomato, pepper and fire truck were probably enough to understand the concept of redness. Once we catch what the red colour is we can correctly identify it on flowers, cars, abstract paintings and also on many real-world objects that we’ve never come across before. This is transfer learning.

We had a pleasure to win the first prize in Poleval 2018 for language modeling task. This success has largely resulted from the adaptation we did to ULMFiT architecture by Jeremy Howard and Sebastian Ruder. Below you can find a short presentation pointing the recent changes to the Language Modeling, especially the crucial improvement of polish language model and n-waves contribution to this:)

It’s been more than a month since the news about the human-like model to generate text (GPT-2) hit the media., If you haven’t paid much attention to this topic here is a short summary with useful reference materials.

Since yesterday we have a deep learning model that is able to generate fairy tales that are consistent and almost completely logical. You could easily read such stories to your kids and this is terrifying news.

Recently our company, n-waves, has won Poleval, national NLP competition. I’d like to share with you some resource without which it wouldn’t have been possible: the fastai library, fast.ai’s courses, and the community around them. If you’re struggling with finding an acceptable service to address your automation needs or if you are interested in applying recent breakthroughs in artificial intelligence, then these resources can also work for you.

HR is often mentioned as one of the most certain fields to see AI in action. With high expectations there come the doubts that it is all a little bit misleading. What are the “can” and “cant’s” of AI in Human Resources? Read our short summary.

While AI is on everyone’s lips nowadays, yet very few people know its origin and reasons for the sudden rise. How the abandoned technology that turned out to be a disappointment in the seventies comes back triumphantly since a few years ago, see in this episode of Bloomberg's "Hello World.” Besides the history and most recognisable faces of AI world served nicely and entertainingly - there are also fact-based predictions on how AI change our world quite soon.

Artificial Intelligence (AI) is a research field focused on creating solutions that can independently make decisions and actions aimed at a specific result. If it scared you a little, you probably remembered movies or fantasy books about robots taking over control of the world. No wonder. Research and development of AI have been ongoing since the 50 of the last century, with the computers’ development. First thoughts in mass culture about AI were a reflection of the fears that accompanied the generations living in the shadow of the Cold War and arms races. But what really is AI?